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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 29 Dec 2009 02:18:05 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/29/t1262078345zpp64jvt4evmh5x.htm/, Retrieved Fri, 03 May 2024 13:18:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71066, Retrieved Fri, 03 May 2024 13:18:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
- R  D        [(Partial) Autocorrelation Function] [] [2009-11-27 16:22:38] [9b30bff5dd5a100f8196daf92e735633]
-   PD            [(Partial) Autocorrelation Function] [] [2009-12-29 09:18:05] [54e293c1fb7c46e2abc5c1dda68d8adb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
577992
565464
547344
554788
562325
560854
555332
543599
536662
542722
593530
610763
612613
611324
594167
595454
590865
589379
584428
573100
567456
569028
620735
628884
628232
612117
595404
597141
593408
590072
579799
574205
572775
572942
619567
625809
619916
587625
565742
557274
560576
548854
531673
525919
511038
498662
555362
564591
541657
527070
509846
514258
516922
507561
492622
490243
469357
477580
528379
533590
517945
506174
501866
516141
528222
532638
536322
536535
523597
536214
586570
596594
580523

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71066&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71066&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71066&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.259422.20130.015462
2-0.23425-1.98770.025325
3-0.27593-2.34130.010993
4-0.202339-1.71690.045148
50.0727340.61720.269536
60.2076451.76190.041164
70.0942220.79950.213315
8-0.234227-1.98750.025337
9-0.293461-2.49010.00754
10-0.205849-1.74670.042478
110.2474922.10.019615
120.7586086.4370
130.140511.19230.118536
14-0.232525-1.9730.026165
15-0.273599-2.32160.011545
16-0.191959-1.62880.053859
170.0427760.3630.358848
180.1512141.28310.101787
190.0510770.43340.33301
20-0.250384-2.12460.018528
21-0.26124-2.21670.014902
22-0.145445-1.23410.110582
230.2147751.82240.036271
240.5631154.77825e-06
250.0645730.54790.292721
26-0.236519-2.00690.024256
27-0.235947-2.00210.024522
28-0.151837-1.28840.100869
290.0269510.22870.409879
300.1161120.98520.163901
310.0239820.20350.419661
32-0.231047-1.96050.026904
33-0.205853-1.74670.042475
34-0.094403-0.8010.212874
350.1620261.37480.086723
360.4100713.47960.000428

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.25942 & 2.2013 & 0.015462 \tabularnewline
2 & -0.23425 & -1.9877 & 0.025325 \tabularnewline
3 & -0.27593 & -2.3413 & 0.010993 \tabularnewline
4 & -0.202339 & -1.7169 & 0.045148 \tabularnewline
5 & 0.072734 & 0.6172 & 0.269536 \tabularnewline
6 & 0.207645 & 1.7619 & 0.041164 \tabularnewline
7 & 0.094222 & 0.7995 & 0.213315 \tabularnewline
8 & -0.234227 & -1.9875 & 0.025337 \tabularnewline
9 & -0.293461 & -2.4901 & 0.00754 \tabularnewline
10 & -0.205849 & -1.7467 & 0.042478 \tabularnewline
11 & 0.247492 & 2.1 & 0.019615 \tabularnewline
12 & 0.758608 & 6.437 & 0 \tabularnewline
13 & 0.14051 & 1.1923 & 0.118536 \tabularnewline
14 & -0.232525 & -1.973 & 0.026165 \tabularnewline
15 & -0.273599 & -2.3216 & 0.011545 \tabularnewline
16 & -0.191959 & -1.6288 & 0.053859 \tabularnewline
17 & 0.042776 & 0.363 & 0.358848 \tabularnewline
18 & 0.151214 & 1.2831 & 0.101787 \tabularnewline
19 & 0.051077 & 0.4334 & 0.33301 \tabularnewline
20 & -0.250384 & -2.1246 & 0.018528 \tabularnewline
21 & -0.26124 & -2.2167 & 0.014902 \tabularnewline
22 & -0.145445 & -1.2341 & 0.110582 \tabularnewline
23 & 0.214775 & 1.8224 & 0.036271 \tabularnewline
24 & 0.563115 & 4.7782 & 5e-06 \tabularnewline
25 & 0.064573 & 0.5479 & 0.292721 \tabularnewline
26 & -0.236519 & -2.0069 & 0.024256 \tabularnewline
27 & -0.235947 & -2.0021 & 0.024522 \tabularnewline
28 & -0.151837 & -1.2884 & 0.100869 \tabularnewline
29 & 0.026951 & 0.2287 & 0.409879 \tabularnewline
30 & 0.116112 & 0.9852 & 0.163901 \tabularnewline
31 & 0.023982 & 0.2035 & 0.419661 \tabularnewline
32 & -0.231047 & -1.9605 & 0.026904 \tabularnewline
33 & -0.205853 & -1.7467 & 0.042475 \tabularnewline
34 & -0.094403 & -0.801 & 0.212874 \tabularnewline
35 & 0.162026 & 1.3748 & 0.086723 \tabularnewline
36 & 0.410071 & 3.4796 & 0.000428 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71066&T=1

[TABLE]
[ROW][C]Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]ACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.25942[/C][C]2.2013[/C][C]0.015462[/C][/ROW]
[ROW][C]2[/C][C]-0.23425[/C][C]-1.9877[/C][C]0.025325[/C][/ROW]
[ROW][C]3[/C][C]-0.27593[/C][C]-2.3413[/C][C]0.010993[/C][/ROW]
[ROW][C]4[/C][C]-0.202339[/C][C]-1.7169[/C][C]0.045148[/C][/ROW]
[ROW][C]5[/C][C]0.072734[/C][C]0.6172[/C][C]0.269536[/C][/ROW]
[ROW][C]6[/C][C]0.207645[/C][C]1.7619[/C][C]0.041164[/C][/ROW]
[ROW][C]7[/C][C]0.094222[/C][C]0.7995[/C][C]0.213315[/C][/ROW]
[ROW][C]8[/C][C]-0.234227[/C][C]-1.9875[/C][C]0.025337[/C][/ROW]
[ROW][C]9[/C][C]-0.293461[/C][C]-2.4901[/C][C]0.00754[/C][/ROW]
[ROW][C]10[/C][C]-0.205849[/C][C]-1.7467[/C][C]0.042478[/C][/ROW]
[ROW][C]11[/C][C]0.247492[/C][C]2.1[/C][C]0.019615[/C][/ROW]
[ROW][C]12[/C][C]0.758608[/C][C]6.437[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.14051[/C][C]1.1923[/C][C]0.118536[/C][/ROW]
[ROW][C]14[/C][C]-0.232525[/C][C]-1.973[/C][C]0.026165[/C][/ROW]
[ROW][C]15[/C][C]-0.273599[/C][C]-2.3216[/C][C]0.011545[/C][/ROW]
[ROW][C]16[/C][C]-0.191959[/C][C]-1.6288[/C][C]0.053859[/C][/ROW]
[ROW][C]17[/C][C]0.042776[/C][C]0.363[/C][C]0.358848[/C][/ROW]
[ROW][C]18[/C][C]0.151214[/C][C]1.2831[/C][C]0.101787[/C][/ROW]
[ROW][C]19[/C][C]0.051077[/C][C]0.4334[/C][C]0.33301[/C][/ROW]
[ROW][C]20[/C][C]-0.250384[/C][C]-2.1246[/C][C]0.018528[/C][/ROW]
[ROW][C]21[/C][C]-0.26124[/C][C]-2.2167[/C][C]0.014902[/C][/ROW]
[ROW][C]22[/C][C]-0.145445[/C][C]-1.2341[/C][C]0.110582[/C][/ROW]
[ROW][C]23[/C][C]0.214775[/C][C]1.8224[/C][C]0.036271[/C][/ROW]
[ROW][C]24[/C][C]0.563115[/C][C]4.7782[/C][C]5e-06[/C][/ROW]
[ROW][C]25[/C][C]0.064573[/C][C]0.5479[/C][C]0.292721[/C][/ROW]
[ROW][C]26[/C][C]-0.236519[/C][C]-2.0069[/C][C]0.024256[/C][/ROW]
[ROW][C]27[/C][C]-0.235947[/C][C]-2.0021[/C][C]0.024522[/C][/ROW]
[ROW][C]28[/C][C]-0.151837[/C][C]-1.2884[/C][C]0.100869[/C][/ROW]
[ROW][C]29[/C][C]0.026951[/C][C]0.2287[/C][C]0.409879[/C][/ROW]
[ROW][C]30[/C][C]0.116112[/C][C]0.9852[/C][C]0.163901[/C][/ROW]
[ROW][C]31[/C][C]0.023982[/C][C]0.2035[/C][C]0.419661[/C][/ROW]
[ROW][C]32[/C][C]-0.231047[/C][C]-1.9605[/C][C]0.026904[/C][/ROW]
[ROW][C]33[/C][C]-0.205853[/C][C]-1.7467[/C][C]0.042475[/C][/ROW]
[ROW][C]34[/C][C]-0.094403[/C][C]-0.801[/C][C]0.212874[/C][/ROW]
[ROW][C]35[/C][C]0.162026[/C][C]1.3748[/C][C]0.086723[/C][/ROW]
[ROW][C]36[/C][C]0.410071[/C][C]3.4796[/C][C]0.000428[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71066&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71066&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.259422.20130.015462
2-0.23425-1.98770.025325
3-0.27593-2.34130.010993
4-0.202339-1.71690.045148
50.0727340.61720.269536
60.2076451.76190.041164
70.0942220.79950.213315
8-0.234227-1.98750.025337
9-0.293461-2.49010.00754
10-0.205849-1.74670.042478
110.2474922.10.019615
120.7586086.4370
130.140511.19230.118536
14-0.232525-1.9730.026165
15-0.273599-2.32160.011545
16-0.191959-1.62880.053859
170.0427760.3630.358848
180.1512141.28310.101787
190.0510770.43340.33301
20-0.250384-2.12460.018528
21-0.26124-2.21670.014902
22-0.145445-1.23410.110582
230.2147751.82240.036271
240.5631154.77825e-06
250.0645730.54790.292721
26-0.236519-2.00690.024256
27-0.235947-2.00210.024522
28-0.151837-1.28840.100869
290.0269510.22870.409879
300.1161120.98520.163901
310.0239820.20350.419661
32-0.231047-1.96050.026904
33-0.205853-1.74670.042475
34-0.094403-0.8010.212874
350.1620261.37480.086723
360.4100713.47960.000428






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.259422.20130.015462
2-0.323307-2.74340.003835
3-0.133669-1.13420.130233
4-0.182679-1.55010.062754
50.0843690.71590.238185
60.0472340.40080.344879
7-0.001179-0.010.496021
8-0.255609-2.16890.016696
9-0.120045-1.01860.155899
10-0.231081-1.96080.026887
110.2651292.24970.013763
120.6262315.31371e-06
13-0.253913-2.15450.017273
140.0796160.67560.250739
15-0.10402-0.88260.190184
16-0.027285-0.23150.408783
17-0.081841-0.69440.24482
18-0.15039-1.27610.10301
19-0.071918-0.61020.27181
20-0.028247-0.23970.405628
210.0180220.15290.439445
220.003680.03120.487589
23-0.097053-0.82350.206466
24-0.01654-0.14030.444389
25-0.042464-0.36030.359832
26-0.099357-0.84310.200991
270.0291790.24760.402577
28-0.088199-0.74840.228331
29-0.038493-0.32660.372449
30-0.032886-0.2790.390505
31-0.05822-0.4940.3114
32-0.007938-0.06740.473241
33-0.05135-0.43570.332171
34-0.08106-0.68780.24689
35-0.121703-1.03270.152605
36-0.073586-0.62440.267169

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.25942 & 2.2013 & 0.015462 \tabularnewline
2 & -0.323307 & -2.7434 & 0.003835 \tabularnewline
3 & -0.133669 & -1.1342 & 0.130233 \tabularnewline
4 & -0.182679 & -1.5501 & 0.062754 \tabularnewline
5 & 0.084369 & 0.7159 & 0.238185 \tabularnewline
6 & 0.047234 & 0.4008 & 0.344879 \tabularnewline
7 & -0.001179 & -0.01 & 0.496021 \tabularnewline
8 & -0.255609 & -2.1689 & 0.016696 \tabularnewline
9 & -0.120045 & -1.0186 & 0.155899 \tabularnewline
10 & -0.231081 & -1.9608 & 0.026887 \tabularnewline
11 & 0.265129 & 2.2497 & 0.013763 \tabularnewline
12 & 0.626231 & 5.3137 & 1e-06 \tabularnewline
13 & -0.253913 & -2.1545 & 0.017273 \tabularnewline
14 & 0.079616 & 0.6756 & 0.250739 \tabularnewline
15 & -0.10402 & -0.8826 & 0.190184 \tabularnewline
16 & -0.027285 & -0.2315 & 0.408783 \tabularnewline
17 & -0.081841 & -0.6944 & 0.24482 \tabularnewline
18 & -0.15039 & -1.2761 & 0.10301 \tabularnewline
19 & -0.071918 & -0.6102 & 0.27181 \tabularnewline
20 & -0.028247 & -0.2397 & 0.405628 \tabularnewline
21 & 0.018022 & 0.1529 & 0.439445 \tabularnewline
22 & 0.00368 & 0.0312 & 0.487589 \tabularnewline
23 & -0.097053 & -0.8235 & 0.206466 \tabularnewline
24 & -0.01654 & -0.1403 & 0.444389 \tabularnewline
25 & -0.042464 & -0.3603 & 0.359832 \tabularnewline
26 & -0.099357 & -0.8431 & 0.200991 \tabularnewline
27 & 0.029179 & 0.2476 & 0.402577 \tabularnewline
28 & -0.088199 & -0.7484 & 0.228331 \tabularnewline
29 & -0.038493 & -0.3266 & 0.372449 \tabularnewline
30 & -0.032886 & -0.279 & 0.390505 \tabularnewline
31 & -0.05822 & -0.494 & 0.3114 \tabularnewline
32 & -0.007938 & -0.0674 & 0.473241 \tabularnewline
33 & -0.05135 & -0.4357 & 0.332171 \tabularnewline
34 & -0.08106 & -0.6878 & 0.24689 \tabularnewline
35 & -0.121703 & -1.0327 & 0.152605 \tabularnewline
36 & -0.073586 & -0.6244 & 0.267169 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71066&T=2

[TABLE]
[ROW][C]Partial Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]PACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.25942[/C][C]2.2013[/C][C]0.015462[/C][/ROW]
[ROW][C]2[/C][C]-0.323307[/C][C]-2.7434[/C][C]0.003835[/C][/ROW]
[ROW][C]3[/C][C]-0.133669[/C][C]-1.1342[/C][C]0.130233[/C][/ROW]
[ROW][C]4[/C][C]-0.182679[/C][C]-1.5501[/C][C]0.062754[/C][/ROW]
[ROW][C]5[/C][C]0.084369[/C][C]0.7159[/C][C]0.238185[/C][/ROW]
[ROW][C]6[/C][C]0.047234[/C][C]0.4008[/C][C]0.344879[/C][/ROW]
[ROW][C]7[/C][C]-0.001179[/C][C]-0.01[/C][C]0.496021[/C][/ROW]
[ROW][C]8[/C][C]-0.255609[/C][C]-2.1689[/C][C]0.016696[/C][/ROW]
[ROW][C]9[/C][C]-0.120045[/C][C]-1.0186[/C][C]0.155899[/C][/ROW]
[ROW][C]10[/C][C]-0.231081[/C][C]-1.9608[/C][C]0.026887[/C][/ROW]
[ROW][C]11[/C][C]0.265129[/C][C]2.2497[/C][C]0.013763[/C][/ROW]
[ROW][C]12[/C][C]0.626231[/C][C]5.3137[/C][C]1e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.253913[/C][C]-2.1545[/C][C]0.017273[/C][/ROW]
[ROW][C]14[/C][C]0.079616[/C][C]0.6756[/C][C]0.250739[/C][/ROW]
[ROW][C]15[/C][C]-0.10402[/C][C]-0.8826[/C][C]0.190184[/C][/ROW]
[ROW][C]16[/C][C]-0.027285[/C][C]-0.2315[/C][C]0.408783[/C][/ROW]
[ROW][C]17[/C][C]-0.081841[/C][C]-0.6944[/C][C]0.24482[/C][/ROW]
[ROW][C]18[/C][C]-0.15039[/C][C]-1.2761[/C][C]0.10301[/C][/ROW]
[ROW][C]19[/C][C]-0.071918[/C][C]-0.6102[/C][C]0.27181[/C][/ROW]
[ROW][C]20[/C][C]-0.028247[/C][C]-0.2397[/C][C]0.405628[/C][/ROW]
[ROW][C]21[/C][C]0.018022[/C][C]0.1529[/C][C]0.439445[/C][/ROW]
[ROW][C]22[/C][C]0.00368[/C][C]0.0312[/C][C]0.487589[/C][/ROW]
[ROW][C]23[/C][C]-0.097053[/C][C]-0.8235[/C][C]0.206466[/C][/ROW]
[ROW][C]24[/C][C]-0.01654[/C][C]-0.1403[/C][C]0.444389[/C][/ROW]
[ROW][C]25[/C][C]-0.042464[/C][C]-0.3603[/C][C]0.359832[/C][/ROW]
[ROW][C]26[/C][C]-0.099357[/C][C]-0.8431[/C][C]0.200991[/C][/ROW]
[ROW][C]27[/C][C]0.029179[/C][C]0.2476[/C][C]0.402577[/C][/ROW]
[ROW][C]28[/C][C]-0.088199[/C][C]-0.7484[/C][C]0.228331[/C][/ROW]
[ROW][C]29[/C][C]-0.038493[/C][C]-0.3266[/C][C]0.372449[/C][/ROW]
[ROW][C]30[/C][C]-0.032886[/C][C]-0.279[/C][C]0.390505[/C][/ROW]
[ROW][C]31[/C][C]-0.05822[/C][C]-0.494[/C][C]0.3114[/C][/ROW]
[ROW][C]32[/C][C]-0.007938[/C][C]-0.0674[/C][C]0.473241[/C][/ROW]
[ROW][C]33[/C][C]-0.05135[/C][C]-0.4357[/C][C]0.332171[/C][/ROW]
[ROW][C]34[/C][C]-0.08106[/C][C]-0.6878[/C][C]0.24689[/C][/ROW]
[ROW][C]35[/C][C]-0.121703[/C][C]-1.0327[/C][C]0.152605[/C][/ROW]
[ROW][C]36[/C][C]-0.073586[/C][C]-0.6244[/C][C]0.267169[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71066&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71066&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.259422.20130.015462
2-0.323307-2.74340.003835
3-0.133669-1.13420.130233
4-0.182679-1.55010.062754
50.0843690.71590.238185
60.0472340.40080.344879
7-0.001179-0.010.496021
8-0.255609-2.16890.016696
9-0.120045-1.01860.155899
10-0.231081-1.96080.026887
110.2651292.24970.013763
120.6262315.31371e-06
13-0.253913-2.15450.017273
140.0796160.67560.250739
15-0.10402-0.88260.190184
16-0.027285-0.23150.408783
17-0.081841-0.69440.24482
18-0.15039-1.27610.10301
19-0.071918-0.61020.27181
20-0.028247-0.23970.405628
210.0180220.15290.439445
220.003680.03120.487589
23-0.097053-0.82350.206466
24-0.01654-0.14030.444389
25-0.042464-0.36030.359832
26-0.099357-0.84310.200991
270.0291790.24760.402577
28-0.088199-0.74840.228331
29-0.038493-0.32660.372449
30-0.032886-0.2790.390505
31-0.05822-0.4940.3114
32-0.007938-0.06740.473241
33-0.05135-0.43570.332171
34-0.08106-0.68780.24689
35-0.121703-1.03270.152605
36-0.073586-0.62440.267169


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')